EconPapers    
Economics at your fingertips  
 

Autonomic machine learning platform

Keon Myung Lee, Jaesoo Yoo, Sang-Wook Kim, Jee-Hyong Lee and Jiman Hong

International Journal of Information Management, 2019, vol. 49, issue C, 491-501

Abstract: Acquiring information properly through machine learning requires familiarity with the available algorithms and understanding how they work and how to address the given problem in the best possible way. However, even for machine-learning experts in specific industrial fields, in order to predict and acquire information properly in different industrial fields, it is necessary to attempt several instances of trial and error to succeed with the application of machine learning. For non-experts, it is much more difficult to make accurate predictions through machine learning.

Keywords: Autonomic machine learning platform; Autonomic level; Machine learning; Smart City (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S026840121831154X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ininma:v:49:y:2019:i:c:p:491-501

DOI: 10.1016/j.ijinfomgt.2019.07.003

Access Statistics for this article

International Journal of Information Management is currently edited by Yogesh K. Dwivedi

More articles in International Journal of Information Management from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:ininma:v:49:y:2019:i:c:p:491-501